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  1. Interdisciplinarity in the Making: Models and Methods in Frontier Science.Nancy J. Nersessian - 2022 - Cambridge, MA: MIT.
    A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...)
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  • Série Investigações Filosóficas: Textos Selecionados de Filosofia da Ciência II [Philosophical Investigation Series: Selected Texts on Philosophy of Science II].Luana Poliseli (ed.) - 2021 - Pelotas: Editora da Universidade Federal de Pelotas.
    A Série Investigação Filosófica, uma iniciativa do Núcleo de Ensino e Pesquisa em Filosofia do Departamento de Filosofia da UFPel e do Grupo de Pesquisa Investigação Filosófica do Departamento de Filosofia da UNIFAP, sob o selo editorial do NEPFil online e da Editora da Universidade Federal de Pelotas, com auxílio financeiro da John Templeton Foundation, tem por objetivo precípuo a publicação da tradução para a língua portuguesa de textos selecionados a partir de diversas plataformas internacionalmente reconhecidas, tal como a Stanford (...)
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  • Homepage Eckhart Arnold.Eckhart Arnold (ed.) - 2001 - Munich: Preprint.
    This is my personal homepage. Find my philosophical papers under "Philosophy".
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  • Computer simulation and the philosophy of science.Eric Winsberg - 2009 - Philosophy Compass 4 (5):835-845.
    There are a variety of topics in the philosophy of science that need to be rethought, in varying degrees, after one pays careful attention to the ways in which computer simulations are used in the sciences. There are a number of conceptual issues internal to the practice of computer simulation that can benefit from the attention of philosophers. This essay surveys some of the recent literature on simulation from the perspective of the philosophy of science and argues that philosophers have (...)
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  • Evidence for personalised medicine: mechanisms, correlation, and new kinds of black box.Mary Jean Walker, Justin Bourke & Katrina Hutchison - 2019 - Theoretical Medicine and Bioethics 40 (2):103-121.
    Personalised medicine has been discussed as a medical paradigm shift that will improve health while reducing inefficiency and waste. At the same time, it raises new practical, regulatory, and ethical challenges. In this paper, we examine PM strategies epistemologically in order to develop capacities to address these challenges, focusing on a recently proposed strategy for developing patient-specific models from induced pluripotent stem cells so as to make individualised treatment predictions. We compare this strategy to two main PM strategies—stratified medicine and (...)
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  • Software Intensive Science.John Symons & Jack Horner - 2014 - Philosophy and Technology 27 (3):461-477.
    This paper argues that the difference between contemporary software intensive scientific practice and more traditional non-software intensive varieties results from the characteristically high conditionality of software. We explain why the path complexity of programs with high conditionality imposes limits on standard error correction techniques and why this matters. While it is possible, in general, to characterize the error distribution in inquiry that does not involve high conditionality, we cannot characterize the error distribution in inquiry that depends on software. Software intensive (...)
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  • How Computational Models Predict the Behavior of Complex Systems.John Symons & Fabio Boschetti - 2013 - Foundations of Science 18 (4):809-821.
    In this paper, we argue for the centrality of prediction in the use of computational models in science. We focus on the consequences of the irreversibility of computational models and on the conditional or ceteris paribus, nature of the kinds of their predictions. By irreversibility, we mean the fact that computational models can generally arrive at the same state via many possible sequences of previous states. Thus, while in the natural world, it is generally assumed that physical states have a (...)
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  • Can we trust Big Data? Applying philosophy of science to software.John Symons & Ramón Alvarado - 2016 - Big Data and Society 3 (2).
    We address some of the epistemological challenges highlighted by the Critical Data Studies literature by reference to some of the key debates in the philosophy of science concerning computational modeling and simulation. We provide a brief overview of these debates focusing particularly on what Paul Humphreys calls epistemic opacity. We argue that debates in Critical Data Studies and philosophy of science have neglected the problem of error management and error detection. This is an especially important feature of the epistemology of (...)
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  • Epistemic Entitlements and the Practice of Computer Simulation.John Symons & Ramón Alvarado - 2019 - Minds and Machines 29 (1):37-60.
    What does it mean to trust the results of a computer simulation? This paper argues that trust in simulations should be grounded in empirical evidence, good engineering practice, and established theoretical principles. Without these constraints, computer simulation risks becoming little more than speculation. We argue against two prominent positions in the epistemology of computer simulation and defend a conservative view that emphasizes the difference between the norms governing scientific investigation and those governing ordinary epistemic practices.
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  • Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics.Mikaela Sundberg - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):273-281.
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  • Cultures of simulations vs. cultures of calculations? The development of simulation practices in meteorology and astrophysics.Mikaela Sundberg - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):273-281.
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  • Creating Convincing Simulations in Astrophysics. [REVIEW]Mikaela Sundberg - 2012 - Science, Technology, and Human Values 37 (1):64-87.
    Numerical simulations have come to be widely used in scientific work. Like experiments, simulations generate large quantities of numbers that require analysis and constant concern with uncertainty and error. How do simulationists convince themselves, and others, about the credibility of output? The present analysis reconstructs the perspectives related to performing numerical simulations, in general, and the situations in which simulationists deal with uncertain output, in particular. Starting from a distinction between idealized and realistic simulations, the paper presents the principal methods (...)
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  • Metaphysics within Chemical Physics: The Case of Ab Initio Molecular Dynamics. [REVIEW]Carsten Seck - 2012 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 43 (2):361-375.
    This paper combines naturalized metaphysics and a philosophical reflection on a recently evolving interdisciplinary branch of quantum chemistry, ab initio molecular dynamics. Bridging the gaps among chemistry, physics, and computer science, this cutting-edge research field explores the structure and dynamics of complex molecular many-body systems through computer simulations. These simulations are allegedly crafted solely by the laws of fundamental physics, and are explicitly designed to capture nature as closely as possible. The models and algorithms employed, however, involve many approximations and (...)
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  • The Heuristic Defense of Scientific Models: An Incentive-Based Assessment.Armin W. Schulz - 2015 - Perspectives on Science 23 (4):424-442.
    It is undeniable that much scientific work is model-based. Despite this, the justification for this reliance on models is still controversial. A particular difficulty here is the fact that many scientific models are based on assumptions that do not describe the exact details of many or even any empirical situations very well. This raises the question of why it is that, despite their frequent lack of descriptive accuracy, employing models is scientifically useful.One..
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  • A practical philosophy of complex climate modelling.Gavin A. Schmidt & Steven Sherwood - 2015 - European Journal for Philosophy of Science 5 (2):149-169.
    We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project. We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naïve predictions. The (...)
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  • Model Organisms as Scientific Representations.Lorenzo Sartori - forthcoming - British Journal for the Philosophy of Science.
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  • What is a Computer Simulation? A Review of a Passionate Debate.Nicole J. Saam - 2017 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 48 (2):293-309.
    Where should computer simulations be located on the ‘usual methodological map’ which distinguishes experiment from theory? Specifically, do simulations ultimately qualify as experiments or as thought experiments? Ever since Galison raised that question, a passionate debate has developed, pushing many issues to the forefront of discussions concerning the epistemology and methodology of computer simulation. This review article illuminates the positions in that debate, evaluates the discourse and gives an outlook on questions that have not yet been addressed.
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  • Kuhn vs. Popper on criticism and dogmatism in science, part II: How to strike the balance.Darrell P. Rowbottom - 2013 - Studies in History and Philosophy of Science Part A 44 (2):161-168.
    This paper is a supplement to, and provides a proof of principle of, Kuhn vs. Popper on Criticism and Dogmatism in Science: A Resolution at the Group Level. It illustrates how calculations may be performed in order to determine how the balance between different functions in science—such as imaginative, critical, and dogmatic—should be struck, with respect to confirmation (or corroboration) functions and rules of scientific method.
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  • Approximations, Idealizations and 'Experiments' at the Physics-Biology Interface.Darrell Patrick Rowbottom - 2008 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 42 (2):145-154.
    This paper, which is based on recent empirical research at the University of Leeds, the University of Edinburgh, and the University of Bristol, presents two difficulties which arise when condensed matter physicists interact with molecular biologists: (1) the former use models which appear to be too coarse-grained, approximate and/or idealized to serve a useful scientific purpose to the latter; and (2) the latter have a rather narrower view of what counts as an experiment, particularly when it comes to computer simulations, (...)
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  • Approximations, idealizations and ‘experiments’ at the physics–biology interface.Darrell Patrick Rowbottom - 2008 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 42 (2):145-154.
    This paper, which is based on recent empirical research at the University of Leeds, the University of Edinburgh, and the University of Bristol, presents two difficulties which arise when condensed matter physicists interact with molecular biologists: the former use models which appear to be too coarse-grained, approximate and/or idealized to serve a useful scientific purpose to the latter; and the latter have a rather narrower view of what counts as an experiment, particularly when it comes to computer simulations, than the (...)
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  • The Epistemic Importance of Technology in Computer Simulation and Machine Learning.Michael Resch & Andreas Kaminski - 2019 - Minds and Machines 29 (1):1-9.
    Scientificity is essentially methodology. The use of information technology as methodological instruments in science has been increasing for decades, this raises the question: Does this transform science? This question is the subject of the Special Issue in Minds and Machines “The epistemological significance of methods in computer simulation and machine learning”. We show that there is a technological change in this area that has three methodological and epistemic consequences: methodological opacity, reproducibility issues, and altered forms of justification.
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  • Computer Modeling and Simulation: Increasing Reliability by Disentangling Verification and Validation.Vitaly Pronskikh - 2019 - Minds and Machines 29 (1):169-186.
    Verification and validation of computer codes and models used in simulations are two aspects of the scientific practice of high importance that recently have been discussed widely by philosophers of science. While verification is predominantly associated with the correctness of the way a model is represented by a computer code or algorithm, validation more often refers to the model’s relation to the real world and its intended use. Because complex simulations are generally opaque to a practitioner, the Duhem problem can (...)
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  • A Minimalist Epistemology for Agent-Based Simulations in the Artificial Sciences.Giuseppe Primiero - 2019 - Minds and Machines 29 (1):127-148.
    The epistemology of computer simulations has become a mainstream topic in the philosophy of technology. Within this large area, significant differences hold between the various types of models and simulation technologies. Agent-based and multi-agent systems simulations introduce a specific constraint on the types of agents and systems modelled. We argue that such difference is crucial and that simulation for the artificial sciences requires the formulation of its own specific epistemological principles. We present a minimally committed epistemology which relies on the (...)
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  • New Issues for New Methods: Ethical and Editorial Challenges for an Experimental Philosophy.Andrea Polonioli - 2017 - Science and Engineering Ethics 23 (4):1009-1034.
    This paper examines a constellation of ethical and editorial issues that have arisen since philosophers started to conduct, submit and publish empirical research. These issues encompass concerns over responsible authorship, fair treatment of human subjects, ethicality of experimental procedures, availability of data, unselective reporting and publishability of research findings. This study aims to assess whether the philosophical community has as yet successfully addressed such issues. To do so, the instructions for authors, submission process and published research papers of 29 main (...)
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  • Agent-based Models as Fictive Instantiations of Ecological Processes.Steven L. Peck - 2012 - Philosophy, Theory, and Practice in Biology 4 (20130604).
    Frigg and Reiss (2009) argue that philosophical problems in simulation bear enough resemblance to recognized issues in the philosophy of modeling that they only pose challenges analogous to those found in standard analytic models used to represent natural systems. They suggest that there are no new philosophical problems in computer simulation modeling beyond those found in traditional mathematical modeling. Winsberg (2009) has countered that there appear to be genuinely new epistemological problems in simulation modeling because the knowledge obtained from them (...)
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  • Real and Virtual Clinical Trials: A Formal Analysis.Barbara Osimani, Marta Bertolaso, Roland Poellinger & Emanuele Frontoni - 2018 - Topoi 38 (2):411-422.
    If well-designed, the results of a Randomised Clinical Trial can justify a causal claim between treatment and effect in the study population; however, additional information might be needed to carry over this result to another population. RCTs have been criticized exactly on grounds of failing to provide this sort of information Evidence, inference and enquiry. Oxford University Press, New York, 2011), as well as to black-box important details regarding the mechanisms underpinning the causal law instantiated by the RCT result. On (...)
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  • Knowledge as the Working and Walking Narrative.Femi Richard Omotoyi̇nbo - 2019 - Beytulhikme An International Journal of Philosophy 8 (2):441-453.
    ‘Motion’ in the acquisition of knowledge is the focus of this paper. My claim is that the motion in the acquisition of knowledge, albeit abstract, is of two dimensions: one as ‘the mind working towards reality’ and the other as ‘reality walking towards the mind’. Using an epistemic approach, I conceptualize these two dimensions (hereafter as the working and walking narrative) under the Externalism and the Internalism divide and identify that externalism leaves us with more to explore about knowledge acquisition (...)
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  • A Puzzle concerning Compositionality in Machines.Ryan M. Nefdt - 2020 - Minds and Machines 30 (1):47-75.
    This paper attempts to describe and address a specific puzzle related to compositionality in artificial networks such as Deep Neural Networks and machine learning in general. The puzzle identified here touches on a larger debate in Artificial Intelligence related to epistemic opacity but specifically focuses on computational applications of human level linguistic abilities or properties and a special difficulty with relation to these. Thus, the resulting issue is both general and unique. A partial solution is suggested.
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  • Computer simulations and experiments: The case of the Higgs boson.Michela Massimi & Wahid Bhimji - 2015 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 51 (C):71-81.
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  • Mesoscopic modeling as a cognitive strategy for handling complex biological systems.Miles MacLeod & Nancy J. Nersessian - 2019 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 78:101201.
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  • Holism, or the Erosion of Modularity: A Methodological Challenge for Validation.Johannes Lenhard - 2018 - Philosophy of Science 85 (5):832-844.
    Modularity is a key concept in building and evaluating complex simulation models. My main claim is that in simulation modeling modularity degenerates for systematic methodological reasons. Consequently, it is hard, if not impossible, to accessing how representational structure and dynamical properties of a model are related. The resulting problem for validating models is one of holism. The argument will proceed by analyzing the techniques of parameterization, tuning, and kludging. They are – to a certain extent – inevitable when building complex (...)
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  • Science in the Age of Computer Simulation – By Eric Winsberg.Jesper Jerkert - 2012 - Theoria 78 (2):168-175.
    QC 20120521. Review of 'Science in the Age of Computer Simulation' by Eric Winsberg.
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  • Verification and Validation of Simulations Against Holism.Julie Jebeile & Vincent Ardourel - 2019 - Minds and Machines 29 (1):149-168.
    It has been argued that the Duhem problem is renewed with computational models since model assumptions having a representational aim and computational assumptions cannot be tested in isolation. In particular, while the Verification and Validation methodology is supposed to prevent such holism, Winsberg argues that verification and validation cannot be separated in practice. Morrison replies that Winsberg overstates the entanglement between the steps. The paper aims at arbitrating these two positions, by stressing their respective validity in relation to domains of (...)
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  • Computer Image Processing: An Epistemological Aid in Scientific Investigation.Vincent Israel-Jost - 2016 - Perspectives on Science 24 (6):669-695.
    In many scientific fields, today’s practices of empirical enquiry rely heavily on the production of images that display the investigated phenomena. And while scientific images of phenomena have been important for a long time, what is striking now is that scientists have found ways to visualize such widely different types of phenomena. In the past twenty or thirty years, we have become accustomed to seeing images of galaxies, of cells, of the human brain but also of blood flow or of (...)
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  • Simulations, Explanation, Understanding: An Analytical Overview.Cyrille Imbert - 2017 - Philosophia Scientiae 21:49-109.
    J’analyse dans cet article la valeur explicative que peuvent avoir les simulations numériques. On rencontre en effet souvent l’affirmation selon laquelle les simulations permettent de prédire, de reproduire ou d’imiter des phénomènes, mais guère de les expliquer. Les simulations rendraient aussi possible l’étude du comportement d’un système par la force brute du calcul mais n’apporteraient pas une compréhension réelle de ce système et de son comportement. Dans tous les cas, il semble que, à tort ou à raison, les simulations posent, (...)
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  • Mapping an expanding territory: computer simulations in evolutionary biology.Philippe Huneman - 2014 - History and Philosophy of the Life Sciences 36 (1):60-89.
    The pervasive use of computer simulations in the sciences brings novel epistemological issues discussed in the philosophy of science literature since about a decade. Evolutionary biology strongly relies on such simulations, and in relation to it there exists a research program (Artificial Life) that mainly studies simulations themselves. This paper addresses the specificity of computer simulations in evolutionary biology, in the context (described in Sect. 1) of a set of questions about their scope as explanations, the nature of validation processes (...)
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  • The philosophical novelty of computer simulation methods.Paul Humphreys - 2009 - Synthese 169 (3):615 - 626.
    Reasons are given to justify the claim that computer simulations and computational science constitute a distinctively new set of scientific methods and that these methods introduce new issues in the philosophy of science. These issues are both epistemological and methodological in kind.
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  • Mutant mice: Experimental organisms as materialised models in biomedicine.Lara Huber & Lara K. Keuck - 2013 - Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences 44 (3):385-391.
    Animal models have received particular attention as key examples of material models. In this paper, we argue that the specificities of establishing animal models—acknowledging their status as living beings and as epistemological tools—necessitate a more complex account of animal models as materialised models. This becomes particularly evident in animal-based models of diseases that only occur in humans: in these cases, the representational relation between animal model and human patient needs to be generated and validated. The first part of this paper (...)
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  • Understanding and misunderstanding computer simulation: The case of atmospheric and climate science—An introduction.Matthias Heymann - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):193-200.
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  • Understanding and misunderstanding computer simulation: The case of atmospheric and climate science—An introduction.Matthias Heymann - 2010 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 41 (3):193-200.
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  • Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions.Casey Helgeson, Vivek Srikrishnan, Klaus Keller & Nancy Tuana - 2021 - Philosophy of Science 88 (2):213-233.
    For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many ti...
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  • Epistemological Issues Concerning Computer Simulations in Science and Their Implications for Science Education.Ileana M. Greca, Eugenia Seoane & Irene Arriassecq - 2014 - Science & Education 23 (4):897-921.
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  • Conceptual and Computational Mathematics†.Nicolas Fillion - 2019 - Philosophia Mathematica 27 (2):199-218.
    ABSTRACT This paper examines consequences of the computer revolution in mathematics. By comparing its repercussions with those of conceptual developments that unfolded in the nineteenth century, I argue that the key epistemological lesson to draw from the two transformative periods is that effective and successful mathematical practices in science result from integrating the computational and conceptual styles of mathematics, and not that one of the two styles of mathematical reasoning is superior. Finally, I show that the methodology deployed by applied (...)
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  • Large-Scale Brain Simulation and Disorders of Consciousness. Mapping Technical and Conceptual Issues.Michele Farisco, Jeanette H. Kotaleski & Kathinka Evers - 2018 - Frontiers in Psychology 9.
    Modelling and simulations have gained a leading position in contemporary attempts to describe, explain, and quantitatively predict the human brain's operations. Computer models are highly sophisticated tools developed to achieve an integrated knowledge of the brain with the aim of overcoming the actual fragmentation resulting from different neuroscientific approaches. In this paper we investigate plausibility of simulation technologies for emulation of consciousness and the potential clinical impact of large-scale brain simulation on the assessment and care of disorders of consciousness, e.g. (...)
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  • What is a Simulation Model?Juan M. Durán - 2020 - Minds and Machines 30 (3):301-323.
    Many philosophical accounts of scientific models fail to distinguish between a simulation model and other forms of models. This failure is unfortunate because there are important differences pertaining to their methodology and epistemology that favor their philosophical understanding. The core claim presented here is that simulation models are rich and complex units of analysis in their own right, that they depart from known forms of scientific models in significant ways, and that a proper understanding of the type of model simulations (...)
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  • Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism.Juan M. Durán & Nico Formanek - 2018 - Minds and Machines 28 (4):645-666.
    Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations :483–496, 2009; Morrison in Philos Stud 143:33–57, 2009), the nature of computer data Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013; Humphreys, in: Durán, Arnold Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013), and the explanatory power of (...)
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  • A Formal Framework for Computer Simulations: Surveying the Historical Record and Finding Their Philosophical Roots.Juan M. Durán - 2019 - Philosophy and Technology 34 (1):105-127.
    A chronicled approach to the notion of computer simulations shows that there are two predominant interpretations in the specialized literature. According to the first interpretation, computer simulations are techniques for finding the set of solutions to a mathematical model. I call this first interpretation the problem-solving technique viewpoint. In its second interpretation, computer simulations are considered to describe patterns of behavior of a target system. I call this second interpretation the description of patterns of behavior viewpoint of computer simulations. This (...)
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  • A Formal Framework for Computer Simulations: Surveying the Historical Record and Finding Their Philosophical Roots.Juan M. Durán - 2019 - Philosophy and Technology 34 (1):105-127.
    A chronicled approach to the notion of computer simulations shows that there are two predominant interpretations in the specialized literature. According to the first interpretation, computer simulations are techniques for finding the set of solutions to a mathematical model. I call this first interpretation the problem-solving technique viewpoint. In its second interpretation, computer simulations are considered to describe patterns of behavior of a target system. I call this second interpretation the description of patterns of behavior viewpoint of computer simulations. This (...)
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  • Hawking radiation and analogue experiments: A Bayesian analysis.Radin Dardashti, Stephan Hartmann, Karim P. Y. Thébault & Eric Winsberg - 2019 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 67:1-11.
    We present a Bayesian analysis of the epistemology of analogue experiments with particular reference to Hawking radiation. Provided such experiments can be externally validated via universality arguments, we prove that they are confirmatory in Bayesian terms. We then provide a formal model for the scaling behaviour of the confirmation measure for multiple distinct realisations of the analogue system and isolate a generic saturation feature. Finally, we demonstrate that different potential analogue realisations could provide different levels of confirmation. Our results thus (...)
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  • The World in the Model: How Economists Work and Think, Mary S. Morgan. Cambridge University Press, 2012, xvii + 421 pages. [REVIEW]François Claveau - 2015 - Economics and Philosophy 31 (1):161-168.
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